23 citations · 23 across the 6 of their papers we have counts for
6 papers
High-Energy Concentration for Federated Learning in Frequency Domain
Haozhi Shi, Weiying Xie, Hangyu Ye +4
Federated Learning (FL) presents significant potential for collaborative optimization without data sharing. Since synthetic data is sent to the server, leveraging the popular conce…
HeteroTune: Efficient Federated Learning for Large Heterogeneous Models
Ruofan Jia, Weiying Xie, Jie Lei +3
While large pre-trained models have achieved impressive performance across AI tasks, their deployment in privacy-sensitive and distributed environments remains challenging. Federat…
FedFQ: Federated Learning with Fine-Grained Quantization
Haowei Li, Weiying Xie, Hangyu Ye +3
Federated learning (FL) is a decentralized approach, enabling multiple participants to collaboratively train a model while ensuring the protection of data privacy. The transmission…
Exploring Hyperspectral Anomaly Detection with Human Vision: A Small Target Aware Detector
Jitao Ma, Weiying Xie, Yunsong Li
Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ from the background. HAD is essential in scenarios of unknown or camouflaged targ…
RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation
Weiying Xie, Zixuan Wang, Jitao Ma +2
Distributed deep learning has recently been attracting more attention in remote sensing (RS) applications due to the challenges posed by the increased amount of open data that are…
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly Detection
Jitao Ma, Weiying Xie, Yunsong Li +1
Hyperspectral anomaly detection (HAD) is widely used in Earth observation and deep space exploration. A major challenge for HAD is the complex background of the input hyperspectral…